Judith Curry points us to a new paper in the journal Water Resources Research, which looks to provide some confirmation of things we have been saying here at BH for some time:

We analyze long-term fluctuations of rainfall extremes in 268 years of daily observations (Padova, Italy, 1725-2006), to our knowledge the longest existing instrumental time series of its kind. We identify multidecadal oscillations in extremes estimated by fitting the GEV distribution, with approximate periodicities of about 17-21 years, 30-38 years, 49-68 years, 85-94 years, and 145-172 years. The amplitudes of these oscillations far exceed the changes associated with the observed trend in intensity. This finding implies that, even if climatic trends are absent or negligible, rainfall and its extremes exhibit an apparent non-stationarity if analyzed over time intervals shorter than the longest periodicity in the data (about 170 years for the case analyzed here). These results suggest that, because long-term periodicities may likely be present elsewhere, in the absence of observational time series with length comparable to such periodicities (possibly exceeding one century), past observations cannot be considered to be representative of future extremes. We also find that observed fluctuations in extreme events in Padova are linked to the North Atlantic Oscillation: increases in the NAO Index are on average associated with an intensification of daily extreme rainfall events. This link with the NAO global pattern is highly suggestive of implications of general relevance: long-term fluctuations in rainfall extremes connected with large-scale oscillating atmospheric patterns are likely to be widely present, and undermine the very basic idea of using a single stationary distribution to infer future extremes from past observations.

The intuition of an ex-oxfordshire housewife says if you don't know whether you have a 17 yr or 21 yr cycle out of 268 yrs, you may be fooling yourself. If I had a penny for every cycle I've seen touted during my time following the climate debate, I'd have..well..a lot of pennies.

Hmmm, nice work done I am sure, but they make assumptions which may not be valid.

Why are the low frequency oscillations assumed to be indicative of a non-stationary process? Far more likely, given the spread of peaks, that these are caused by a process with stationary, fractal dynamics. Yes they correlate with weather patterns, but given the weather patterns themselves do not have a predictability either, and given that correlation is not causation (more correctly, these things have common cause, imprinted on the fractal dynamics of the system), it is quite incorrect to assume these changes are direct evidence of any kind of non-stationarity.

I would encourage Marco and Stefano to have a long chat with Alberto Montanari to widen their horizons on fractal dynamics and stationarity.

The conclusions regarding natural dynamics are good and a pointer in the right direction, if only the technical term non-stationary was not so misused, I would also be recommending this paper...

A demonstration that if you properly examine complex data in a number of different ways, you could derive multiple patterns within that data. Makes a refreshing change from correcting, then modelling, the data to demonstrate that it fails to contradict the desired hypothesis.

"Yes. The climate is already starting to become different to that previously seen in the instrumental record - not enormously different yet, but changes are becoming evident. And its clear that change (to some extent or other) will continue."

I requested that Richard direct me to evidence of statistically significant changes in climate extremes based on observational data. I am still waiting for an answer. The paper in Water Resources Research is a good reminder that leading IPCC authors such as Richard Betts should not make assertions about climate based on anecdotal information.

Tim Palmer who, as the Bish notes, got a gong in the New year's honours list published a paper in April on reliability of seasonal climate forecasts, including precipitation.

Skimming through it, I was pleasantly surprised to see that his categorisations of skill really did include some very frank assessments. For example, the 'best regarded' rainfall predictions for various polar regions and the UK varied from "Marginally useful" through "Not useful" to "Dangerously Useless".

potentillaLike you I have been waiting (fortunately not holding my breath!) for some time for observational evidence of a variety of the claims being made about the disasters that are always just round the next corner.But your use of the word 'anecdotal' set me off on another train of thought.Apropos the temperature record and the question of ocean pH (currently under discussion on Unthreaded), since the measurements in each case are (in the case of temperature) limited to relatively few locations across the surface of the earth with large gaps and huge variation in the siting of the instruments and in the case of pH the virtual impossibility of accurately sampling something which covers three-quarters of the earth's surface to a depth, in some places, of several miles, are these observations in effect any better than anecdotal?And if not why should we pay any attention to them?

I am researching CET from its instrumental end of 1659 back to the domesday book.

Generally, unless it suits them, the met office definition of instrumental records is from 1910 or on rare occasions David Parkers 1772 series.

What strikes me is that weather definitely goes in cycles, using the word loosely, with for example a decade of dry years or wet years or stormy years followed by decades of a different character.

By far the most noticeable feature in the record ate the extreme weather events as typified by ferocious storms and extreme rainfall events. Snowfall is much less of a feature.

The bridges in the met offices home city of Exeter were often swept Away by floodimg caused by many weeks or months of heavy rain. . Weather has been generally more benign, with exceptions of course , in the post 1850 period than the centuries prior to this.

I don't have a problem with the temperature records but am certainly suspicious of claims made about ocean pH with so little representative data. However, most of the assertions regarding increased frequency of extreme weather are anecdotal. While one might excuse unqualified Guardian environmental reporters for wild extrapolation and speculation, it appalls me that so many climate scientists make similar anecdotal comments without adequate statistical evidence. The Hurst Phenomenon, which characterizes persistence in the climate, has been known since the 1950s and the Water Resources Research paper is yet another confirmation. As a New Year re-gift, here is Geoff Chambers on John Vidal:

"John Vidal, the Guardian’s Environmental editor, who can write an eyewitness report on the effects of climate change in Tanzania (complete with desperate quotes from the locals) while staring out of the plane window on a flight to Pretoria."

"There is no statistically significant evidence for the existence of a pause,"

What? Well, I suppose it's right because there is no convincing evidence that anything is happening which is capable of pausing. One has to allow the supposition of a trend before one can claim a pause. So EM is right, but we don't have a problem either until the observations depart far enough from the assumed model to show statistically. And that only disproves that particular (statistical, not GCM) model.

Or not. I'm only an ex-oxfordshire housewife, and I know no statistics.

You don't need to know statistics to apply common sense as demonstrated by our ex-Oxfordshire housewife. The only issue with the pause is one of GCM model validation. The model calibrations with past average world temperatures were excellent which would be expected as there were enough parameter tuning knobs. But models are potentially misleading until validated. More info here:http://climateaudit.org/2014/12/11/unprecedented-model-discrepancy/

Can someone in the know explain:"approximate periodicities of about..,30-38 years" Does that mean that the period might be variable? It doesn't seem to be saying that ( if 'about' = 'approximate' and so a tautology ) but I thought that everyone ( at least since Bruckner in 1890s) saw these oscillations as variable in their period.

I have read it several times, now, and was waiting to see if anyone else could shed a little light onto it for me. It just seems an awful lot of verbiage with actually nothing being said – basically, “Our records show that it rains: sometimes, quite a lot; other times, not so much. Our next study is to reveal which way is ‘up’. Please give generously.”

The 17-21 year cycle in rainfall is most likely due to the precession of the lunar orbit with a period of 18.6y . This changes the maximum latitude that the moon reaches during its orbit of the earth and as a consequence the tidal forces acting on the Jet Stream. There are several papers reporting similar cycles of drought from China & N. America

Potentilla refers to the Guardian correspondent filing his report climate change in Tanzania flying at 30000ft ,although it galls me to agree with the correspondent him on this occasion.

Over 90% of the forests in East Africa have been cleared in the last 70 years. It is reasonable to conclude that this will have a lasting influence on the regional climate. However, apart from the loss of the CO2 take up by the trees very little of this anthropogenic climate change can be attributed to an increase global CO2 emissions

Paul, re-reading the abstract I may have been a little harsh, but the confusion is a common one in climate science and the way the abstract is worded could foster this misunderstanding. (For those not familiar with my views on the topic, see Harry Lins' perspective

http://www.whycos.org/chy14/download/file.php?id=13

The reason I think I may have been harsh is that they describe the low frequency fluctuations as an "apparent" non-stationarity, so they are recognising that low frequency fluctuations automatically imply non-stationarity, but in doing so also reinforce a very common misconception found across climate articles, that when one sees fluctuation or change, non-stationarity is the first thing thought of.

They go on in the abstract to say:

long-term fluctuations in rainfall extremes connected with large-scale oscillating atmospheric patterns are likely to be widely present, and undermine the very basic idea of using a single stationary distribution to infer future extremes from past observations.

I think using a single stationary distribution may well be fine, the challenge is that there is enormous uncertainty in inferring it from past observations. Perhaps that is what they intended to say, but the writing is very ambiguous.

Unfortunately, I am reading far too much from the abstract alone since I have not downloaded the article, and I am aware that messages are often over simplified in abstracts, so I should reserve judgement until reading the article more thoroughly.

Torrental rains in the Channel,the North Sea or the Irish Sea the only people that notice are trawlerman ferry passengers and workers on North Sea oil rigs . If it rains hard on lands where everything is built on a flood plains and all the local flooded out residents have mobile phone footages posted on twitter than everyone is going to hear about it.

There is no accurate way of measuring rainfall out at sea or on land only with blanket continuous coverage with weather radar.

The lead author, Marco Marani, has a background in hydrology and hydrodynamics rather than "climate science". Standard practice in hydrology is to assume that the GEV (or similar) distribution can be applied to extreme events and hence estimates can be made of the 100-year flood for example. Implicit in flood and rainfall frequency analysis is that the GEV distribution can be calculated from past historical observations and thus stationarity is also implicitly assumed. While we all know the climate is non-stationary, we are stuck with assuming stationarity unless a statistically significant trend can be detected in the data. So far I have not come across any trends in extreme values that are statistically significant.

My understanding of the paper is that they did a series of frequency analyses for different periods and detected multidecadal oscillations in extremes. This is of great interest to hydrologists as we are usually limited to periods of record less than 100 years, considerably less than the 268 years they used.

268 years at 36597,820 observations = 97,820 observations.At one observation per day, I would call that a high sample rate.CD's use 44,100 samples per second. Which is actually the minimum standard in music signal processing. Music recording and signal processing would more likely be done at 48,000 and above.